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@@ -712,8 +712,8 @@ def merge_sliced_parameter(sliced_parameters, strategy=None): |
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Args: |
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sliced_parameters (list[Parameter]): Parameter slices in order of rank_id. |
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strategy (dict): Parameter slice strategy. Default: None. |
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If strategy is None, just merge parameter slices in 0 axis order. |
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strategy (dict): Parameter slice strategy, the default is None. |
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If strategy is None, just merge parameter slices in 0 axis order. |
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- key (str): Parameter name. |
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- value (<class 'node_strategy_pb2.ParallelLayouts'>): Slice strategy of this parameter. |
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@@ -728,11 +728,15 @@ def merge_sliced_parameter(sliced_parameters, strategy=None): |
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Examples: |
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>>> strategy = build_searched_strategy("./strategy_train.ckpt") |
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>>> sliced_parameters = [\ |
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Parameter(Tensor(np.array([0.00023915, 0.00013939, -0.00098059])), "network.embedding_table"), \ |
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Parameter(Tensor(np.array([0.00015815, 0.00015458, -0.00012125])), "network.embedding_table"), \ |
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Parameter(Tensor(np.array([0.00042165, 0.00029692, -0.00007941])), "network.embedding_tabel"), \ |
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Parameter(Tensor(np.array([0.00084451, 0.00089960, -0.00010431])), "network.embedding_table")] |
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>>> sliced_parameters = [ |
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>>> Parameter(Tensor(np.array([0.00023915, 0.00013939, -0.00098059])), |
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>>> "network.embedding_table"), |
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>>> Parameter(Tensor(np.array([0.00015815, 0.00015458, -0.00012125])), |
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>>> "network.embedding_table"), |
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>>> Parameter(Tensor(np.array([0.00042165, 0.00029692, -0.00007941])), |
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>>> "network.embedding_tabel"), |
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>>> Parameter(Tensor(np.array([0.00084451, 0.00089960, -0.00010431])), |
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>>> "network.embedding_table")] |
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>>> merged_parameter = merge_sliced_parameter(sliced_parameters, strategy) |
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""" |
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if not isinstance(sliced_parameters, list): |
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